Smart Agriculture with Mike Prorock

Farms have lots of data. A corn farmer needs to monitor the chemical composition of soil. A soybean farmer needs to track crop yield. A chicken farmer needs to count the number of eggs produced.

If this data is captured, it can be acted upon—for example, a dry farm can automatically turn up its irrigation system. Or the data can simply be studied.

If you work in a pure software business, you might take for granted how easy it is to track your metrics. On the farm, you need to use sensors and drones to gather your data.

Mike Prorock is the CTO of Mesur.io, a company that makes sensors and software infrastructure for agriculture. He joins the show to describe the use cases for agriculture technology, and the architecture behind it.

Today’s episode is a great complement to our recent episodes on streaming data. Mesur.io offers a case study in how streaming systems can be put into practice. Mike will also be speaking at the upcoming Strata Data Conference in San Jose.

Meetups for Software Engineering Daily are being planned! Go to softwareengineeringdaily.com/meetup if you want to register for an upcoming Meetup. In March, I’ll be visiting Datadog in New York and Hubspot in Boston, and in April I’ll be at Telesign in LA.

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I listen to a lot of podcasts about technical content, and the Google Cloud Platform podcast is one of my favorites. The GCP Podcast covers the technologies that Google Cloud is building–through interviews with the people building them. And these are often unique, Google cloud services–like BigQuery, AutoML, and Firebase. I am a big Firebase user, so I try to learn about how it works under the hood, and I want to hear about new features they are releasing. I also listen to the GCP Podcast to prepare for episodes of Software Engineering Daily–because when I do shows about Google Cloud technologies, I am doing research around them, and I find that the GCP Podcast covers topics before I do. So if you want to stay on the leading edge of what is being released at Google, and how these new technologies are built, check out gcppodcast.com. I’ve been a listener for a few years now, and the content is consistently good–a few of my favorite recent episodes are the interview with Vint Cerf and the show about BigQuery. You can find those episodes and more by going to gcppodcast.com.

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There’s a new open source project called Dremio that is designed to simplify analytics. It’s also designed to handle some of the hard work, like scaling performance of analytical jobs. Dremio is the team behind Apache Arrow, a new standard for in-memory columnar data analytics. Arrow has been adopted across dozens of projects – like Pandas – to improve the performance of analytical workloads on CPUs and GPUs. It’s free and open source, designed for everyone, from your laptop, to clusters of over 1,000 nodes. At dremio.com/sedaily you can find all the necessary resources to get started with Dremio for free. If you like it, be sure to tweet @dremiohq and let them know you heard about it from Software Engineering Daily. Thanks again to Dremio, and check out dremio.com/sedaily to learn more.